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Physical Layer Authentication in Wireless Networks-Based Machine Learning Approaches.

Lamia Alhoraibi1, Daniyal Alghazzawi1, Reemah Alhebshi1

  • 1Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah 21589, Saudi Arabia.

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Summary
This summary is machine-generated.

This study systematically reviews physical layer authentication (PLA) in wireless networks. It highlights how machine learning and deep learning enhance PLA security performance, identifying future research directions.

Keywords:
deep learningmachine learningphysical layer authenticationphysical layer securitysignal classificationwireless communication

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Area of Science:

  • Computer Science
  • Electrical Engineering
  • Information Security

Background:

  • Wireless network security is critical due to rapid development and increasing threats.
  • Physical layer authentication (PLA) offers information-theory security and low complexity by leveraging unique device features.
  • A systematic overview of current PLA techniques and foundational principles is lacking.

Purpose of the Study:

  • To systematically review and compare existing studies on physical layer authentication (PLA).
  • To evaluate the impact of machine learning (ML) and deep learning (DL) on PLA security performance in wireless networks.
  • To identify current challenges and propose future research directions in PLA.

Main Methods:

  • Systematic literature review and comparative analysis of existing PLA studies.
  • Evaluation of ML and DL techniques applied to PLA models.
  • Identification of key features and methodologies in PLA research.

Main Results:

  • Machine learning and deep learning approaches significantly enhance wireless network security performance in PLA models.
  • A comprehensive comparison of various PLA techniques and their effectiveness is presented.
  • The study demonstrates the latest advancements and methodologies in PLA.

Conclusions:

  • PLA is a crucial component for robust wireless network security.
  • ML and DL are pivotal in advancing PLA capabilities for enhanced security.
  • Further research is needed to address identified issues and optimize PLA for future wireless systems.